Skip to Main content Skip to Navigation
Poster communications

A comparative study between compressive sensing and conventional speech conding methods

Abstract : Speech coding is an essential procedure in public switched telephone system (PSTN), digital cellular communications, videoconferencing systems, and emerging voice over Internet applications. Compressed sensing is an original signal processing tool for efficiently acquiring and reconstructing a signal, by exploiting its compressibility. In this paper, compressive sensing is employed for speech coding. Particularly in this work and in order to demonstrate its efficiency in speech coding, we propose a comparative study between this method and optimal existing methods, namely, Code-excited linear prediction and LIoyd-Max quantization algorithm. Experimental results indicate that CS method achieve a significant improvements in performances with respect to the aforementioned methods.
Complete list of metadata

https://hal-uphf.archives-ouvertes.fr/hal-03572719
Contributor : Kathleen TORCK Connect in order to contact the contributor
Submitted on : Monday, February 14, 2022 - 1:18:01 PM
Last modification on : Wednesday, June 8, 2022 - 3:30:39 AM

Identifiers

Collections

Citation

Abdelkader Boukhobza, Messaoud Hettiri, Abdelmalik Taleb-Ahmed, Abdennacer Bounoua. A comparative study between compressive sensing and conventional speech conding methods. 1st International Conference on Communications, Control Systems and Signal Processing (CCSSP 2020), May 2020, EL OUED, Algeria. IEEE, pp.215-218, ⟨10.1109/CCSSP49278.2020.9151756⟩. ⟨hal-03572719⟩

Share

Metrics

Record views

20